Senior/Staff Software Engineer, AI Agent Infrastructure

Highlights

• Build the most rigorous closed-loop evaluation system for AI work anywhere.
• Make a production fleet of agents trustworthy, autonomous and more capable.
• Amplify every engineer and researcher's output by 100x with trusted autonomy.

What they offer

• annual performance bonus
• equity
• competitive benefits package

Ideal candidate

You are rigorous about evaluation and obsessed with knowing what is real versus impressive. You thrive end-to-end in ambiguous, high-ownership environments and want to make autonomous work trustworthy enough to run unattended.

Requirements

• Care deeply about evaluation and whether benchmarks measure anything real
• Work end-to-end without needing the problem pre-decomposed
• Hands-on post-training or fine-tuning experience including SFT, preference optimization, RL, distillation and evaluation
• Experience with ML training or research infrastructure including experiment orchestration, evaluation pipelines, hyperparameter search, data pipelines
• Experience running inference serving, cost, or capacity at meaningful scale
• Familiarity with agent architecture patterns including planning, reflection, long-horizon memory, multi-agent coordination
• Experience with open tool-integration protocols, plugin or skill frameworks, and model-routing or gateway layers
• Background in developer experience or platform engineering, observability, or security isolation
• Go, C++, or Rust experience in addition to Python